Today, large communications networks are serviced by more than 30,000 Internet Service Providers (ISPs) across the world, predominantly operating on a commercial basis as a service provider. The services range from the mass-marketing of simple access products to service-intensive operations that provide specialized service levels to more localized internet markets. The present application mainly concerns ISPs providing networks, referred to more generally as network service providers.
With networks playing an ever increasing role in today's electronic economy, an efficient management of the networks and an efficient planning of future modifications is advantageous.
With the rapid growth of network usage, network service providers are currently facing ever increasing expectations from their customers to the quality of service (minimum delay, maximum reliability, high bandwidth for data transfer rates, low costs, etc). The main task is to satisfy the quality of service parameters while maximising the return of investment, i.e. to ensure an efficient utilisation of the available bandwidth in addition, but there are issues relating to future sales, strategic planning and business development. One concerns Service Level Agreements (SLAs) with their customers.
An SLA is a service contract between a network service provider and a subscriber, guaranteeing a particular service's quality characteristics. SLAs usually focus on network availability and data-delivery reliability. Violations of an SLA by a service provider may result in a prorated service rate for the next billing period for the subscriber.
Thus it is important for a network service provider to know whether it can issue an SLA to another customer without violating any existing SLAs. Here it needs to estimate what is the largest new workload that the network can handle with respect to network availability and data-delivery reliability.
In strategic planning, the objective is to investigate how to revise the existing network topology (and connection points to external nodes) such that the resource utilization is minimized and more balanced. The problem is to minimize the resource utilization by determining which backbone links are overloaded, and to add links to the network to redistribute the load. For a given workload, the question is where to add the links in the network and what is the required bandwidth of each backbone link such that the capacity of the new network topology is greater, i.e. can deal with a larger load. Another question concerns which node should be used to connect a new customer to the network. This should be the one which minimises resource utilisation and expands capacity in the most cost effective way.
There are several tools available for planning and optimising communications networks. They are usually based on a discrete event simulation of the network. For this, a typical scenario of end-to-end loads must be provided as input by the user. Starting from this scenario, the tool simulates the transport of the traffic through the network, observing link utilization overload and other events.
End to end traffic data are usually obtained by obtaining probes or router-based information. Such a method is expensive to implement and usually only a part of the whole network is equipped with data collection points. The data collection process has the additional disadvantage that it adds to the traffic congestion of the network.
Such traffic data, if available, may then be used in network modelling or a network simulation. However, most simulations are not based on real data, but only on estimates. The simulation is then used for network planning or optimisation tools. The user usually defines a scenario which is then tested using the simulation tool.
Another approach is described in the applicant's patent application GB 0 028 848, filed on 27 Nov. 2000 (agent reference J42831GB), which is hereby incorporated by reference. In the approach real link traffic data are used to derive end-to-end traffic load intervals. Link traffic data are collected during a limited time period. Thus a “snapshot” of the data traffic is obtained. Data collection may be repeated at certain times or periodically. The results of this process are subsequently used in a traffic flow optimisation system to estimate traffic loads in the given scenario. This approach has the disadvantage that it is difficult to derive meaningful intervals for the end-to-end load in the optimisation process, especially if multiple modifications are to be continued to give a consistent estimate in traffic flow. Another disadvantage of the method is that it is difficult to work from a plurality of traffic flow intervals in the optimisation or planning process.